content stringlengths 22 815k | id int64 0 4.91M |
|---|---|
def test_data_viewer(dataframe):
"""Test DataView functions."""
dt_viewer = DataViewer(data=dataframe)
check.equal(len(dataframe), len(dt_viewer.filtered_data))
_apply_filter(dt_viewer.data_filter, "Account", "contains", "MSTICAlertsWin1")
dt_viewer._apply_filter(btn=None)
check.equal(3, len(dt... | 5,331,300 |
def test_query_xdd():
"""Assert number of records equals expected hits."""
s.build_query_urls()
# Grab first search term
s.next_url = s.search_urls[0]
s.query_xdd()
if s.response_status == "success":
assert s.response_hits == len(s.response_data) | 5,331,301 |
def deceptivemultimodal(x: np.ndarray) -> float:
"""Infinitely many local optima, as we get closer to the optimum."""
assert len(x) >= 2
distance = np.sqrt(x[0]**2 + x[1]**2)
if distance == 0.:
return 0.
angle = np.arctan(x[0] / x[1]) if x[1] != 0. else np.pi / 2.
invdistance = int(1. / ... | 5,331,302 |
def get_basins_scores(memory_array, binarized_cluster_dict, basinscore_method="default"):
"""
Args:
- memory_array: i.e. xi matrix, will be N x K (one memory from each cluster)
- binarized_cluster_dict: {k: N x M array for k in 0 ... K-1 (i.e. cluster index)}
- basinscore_method: options... | 5,331,303 |
def generate_inputs_ph(fixture_sandbox, fixture_localhost, fixture_code, generate_remote_data, generate_kpoints_mesh):
"""Generate default inputs for a `PhCalculation."""
def _generate_inputs_ph():
"""Generate default inputs for a `PhCalculation."""
from aiida.orm import Dict
from aiida... | 5,331,304 |
def escape_url(raw):
"""
Escape urls to prevent code injection craziness. (Hopefully.)
"""
from urllib.parse import quote
return quote(raw, safe="/#:") | 5,331,305 |
def split_sample(labels):
"""
Split the 'Sample' column of a DataFrame into a list.
Parameters
----------
labels: DataFrame
The Dataframe should contain a 'Sample' column for splitting.
Returns
-------
DataFrame
Updated DataFrame has 'Sample' column with a list of strin... | 5,331,306 |
def pmi_odds(pnx, pn, nnx, nn):
"""
Computes the PMI with odds
Args:
pnx (int): number of POSITIVE news with the term x
pn (int): number of POSITIVE news
nnx (int): number of NEGATIVE news with the term x
nn (int): number of NEGATIVE news
Ret... | 5,331,307 |
def berDecodeLength(m, offset=0):
"""
Return a tuple of (length, lengthLength).
m must be atleast one byte long.
"""
l = ber2int(m[offset + 0:offset + 1])
ll = 1
if l & 0x80:
ll = 1 + (l & 0x7F)
need(m, offset + ll)
l = ber2int(m[offset + 1:offset + ll], signed=0)
... | 5,331,308 |
def hasAspect(obj1, obj2, aspList):
""" Returns if there is an aspect between objects
considering a list of possible aspect types.
"""
aspType = aspectType(obj1, obj2, aspList)
return aspType != const.NO_ASPECT | 5,331,309 |
def gen_decomposition(denovo_name, basis_names, weights, output_path, project, \
mtype, denovo_plots_dict, basis_plots_dict, reconstruction_plot_dict, \
reconstruction=False, statistics=None, sig_version=None, custom_text=None):
"""
Generate the correct plot based on mtype.
Parameters:
----------
denovo_name: ... | 5,331,310 |
def org(gh):
"""Creates an Org instance and adds an spy attribute to check for calls"""
ret = Organization(gh, name=ORG_NAME)
ret._gh = Mock(wraps=ret._gh)
ret.spy = ret._gh
return ret | 5,331,311 |
def merge_regions(
out_path: str, sample1_id: int, regions1_file: File, sample2_id: int, regions2_file: File
) -> File:
"""
Merge two sorted region files into one.
"""
def iter_points(regions):
for start, end, depth in regions:
yield (start, "start", depth)
yield (en... | 5,331,312 |
def get_text_hexdigest(data):
"""returns md5 hexadecimal checksum of string/unicode data
NOTE
----
The md5 sum of get_text_hexdigest can differ from get_file_hexdigest.
This will occur if the line ending character differs from being read in
'rb' versus 'r' modes.
"""
data_class = data._... | 5,331,313 |
async def test_get_rdf_turtle(client: Any, fs: Any) -> None:
"""Should return status 200 OK and RDF as turtle."""
contents = '<http://example.com/drewp> <http://example.com/says> "Hello World" .'
fs.create_file(
"/srv/www/static-rdf-server/data/ontology-type-1/ontology-1/ontology-1.ttl",
con... | 5,331,314 |
def rbInsertFixup(T, z):
"""给结点重新着色，将其保持为红黑树"""
RED = RBTree.COLOR_RED
BLACK = RBTree.COLOR_BLACK
while z.p.color == RED:
if z.p == z.p.p.left:
y = z.p.p.right
if y.color == RED:
z.p.color = BLACK
y.color = BLACK
z.p.p.color... | 5,331,315 |
def recipe(recipe_id):
"""
Display the recipe on-page for each recipe id that was requested
"""
# Update the rating if it's an AJAX call
if request.method == "POST":
# check if user is login in order to proceed with rating
if not session:
return json.dumps({'status': 'not... | 5,331,316 |
def api_program_ordering(request, program):
"""Returns program-wide RF-aware ordering (used after indicator deletion on program page)"""
try:
data = ProgramPageIndicatorUpdateSerializer.load_for_pk(program).data
except Program.DoesNotExist:
logger.warning('attempt to access program page orde... | 5,331,317 |
def isinteger(x):
"""
determine if a string can be converted to an integer
"""
try:
a = int(x)
except ValueError:
return False
else:
return True | 5,331,318 |
def unmarshal_tools_pcr_values(
buf: bytes, selections: TPML_PCR_SELECTION
) -> Tuple[int, List[bytes]]:
"""Unmarshal PCR digests from tpm2_quote using the values format.
Args:
buf (bytes): content of tpm2_quote PCR output.
selections (TPML_PCR_SELECTION): The selected PCRs.
Returns:
... | 5,331,319 |
def new_topic(request):
"""添加新主题"""
if request.method != 'POST':
#未提交数据，创建一个新表单
form = TopicForm()
else:
#POST提交的数据，对数据进行处理
form = TopicForm(request.POST)
if form.is_valid():
new_topic = form.save(commit = False)
new_topic.owner = request.user
new_topic.save()
form.save()
return HttpResponse... | 5,331,320 |
def save_model(model, model_filepath):
"""
Save the classifier model to the location specified
Args:
model (model) Classifier Model to save
model_filepath (string) path to model pickle file
"""
pickle.dump(model, open(model_filepath, 'wb')) | 5,331,321 |
def two_lot_2bid_2com_2win(self):
""" Create tender with 2 lots and 2 bids """
self.create_tender(initial_lots=self.test_lots_data * 2)
tenderers = self.create_tenderers(2)
# create bid
self.app.authorization = ("Basic", ("broker", ""))
self.app.post_json(
"/tenders/{}/bids".format(self.... | 5,331,322 |
def address(lst: Union[List[Any], str], dim: Optional[int] = None) -> Address:
"""
Similar to :meth:`Address.fromList`, except the name is shorter, and
the dimension is inferred if possible. Otherwise, an exception is thrown.
Here are some examples:
>>> address('*')
Address(*, 0)
>>> addre... | 5,331,323 |
def import_olx(self, user_id, course_key_string, archive_path, archive_name, language):
"""
Import a course or library from a provided OLX .tar.gz archive.
"""
current_step = 'Unpacking'
courselike_key = CourseKey.from_string(course_key_string)
set_code_owner_attribute_from_module(__name__)
... | 5,331,324 |
async def initialize_agent(request):
""" Initialize agent.
"""
agent = request.app['agent']
data = await request.post()
agent.owner = data['agent_name']
agent.endpoint = data['endpoint']
wallet_name = '%s-wallet' % agent.owner
# pylint: disable=bare-except
# TODO: better handle pot... | 5,331,325 |
def create_scenario_dataframes_geco(scenario):
"""
Reads GECO dataset and creates a dataframe of the given scenario
"""
df_sc = pd.read_csv(io["scenario_geco_path"])
df_sc_europe = df_sc.loc[df_sc["Country"] == "EU28"]
df_scenario = df_sc_europe.loc[df_sc_europe["Scenario"] == scenario]
ret... | 5,331,326 |
def escape_env_var(varname):
"""
Convert a string to a form suitable for use as an environment variable.
The result will be all uppercase, and will have all invalid characters
replaced by an underscore.
The result will match the following regex: [a-zA-Z_][a-zA-Z0-9_]*
Example:
"my.pri... | 5,331,327 |
def from_file(handle, output):
"""
Convert a handle of JSON formatted objects and write a GFF3 file to the
given output handle.
"""
parsed = coord.from_file(handle)
features = regions_as_features(parsed)
write_gff_text(features, output) | 5,331,328 |
def rms(signal):
"""
rms(signal)
Measures root mean square of a signal
Parameters
----------
signal : 1D numpy array
"""
return np.sqrt(np.mean(np.square(signal))) | 5,331,329 |
def get_template_page(page):
"""method used to get the a page based on the theme
it will check the options.theme defined theme for the page first and if it isnt found
it will fallback to options.theme_dir/cling for the template page
"""
templates = ['%s.html' % os.path.join(options.theme_dir, 'clin... | 5,331,330 |
def named_masks(module, prefix=""):
"""Returns an iterator over all masks in the network, yielding both
the name of a maskable submodule as well as its current mask.
Parameters
----------
module : torch.nn.Module
The network, which is scanned for variational modules.
prefix : string, d... | 5,331,331 |
def handle_with_item(items: List[_T],
item_handler: Callable[[_T], _U],
result_handler: Callable[[_T, _U], Any],
pool: Optional[ThreadPool] = None) -> None:
"""
Processes all the items in a separate thread using `item_handler` and post-processes
... | 5,331,332 |
def get_config(
config_path, trained: bool = False, runner="d2go.runner.GeneralizedRCNNRunner"
):
"""
Returns a config object for a model in model zoo.
Args:
config_path (str): config file name relative to d2go's "configs/"
directory, e.g., "COCO-InstanceSegmentation/mask_rcnn_R_50_F... | 5,331,333 |
def make_game(
width: int = defaults.WIDTH,
height: int = defaults.HEIGHT,
max_rooms: int = defaults.MAX_ROOMS,
seed: Optional[int] = defaults.SEED,
slippery_coefficient: float = defaults.SLIPPERY_COEFFICIENT,
default_reward: float = defaults.DEFAULT_REWARD,
goal_reward: float = defaults.GOA... | 5,331,334 |
def weighted_var(x, weights=None):
"""Unbiased weighted variance (sample variance) for the components of x.
The weights are assumed to be non random (reliability weights).
Parameters
----------
x : np.ndarray
1d or 2d with observations in rows
weights : np.ndarray or None
1d ar... | 5,331,335 |
def start_detailed_result_worker_route():
"""
Add detailed result worker if not exist
:return: JSON
"""
# check if worker already exist
if check_worker_result(RABBITMQ_DETAILED_RESULT_QUEUE_NAME) == env.HTML_STATUS.OK.value:
return jsonify(status=env.HTML_STATUS.OK.value)
if 'db_nam... | 5,331,336 |
def test_get_http_response_querystring_payload():
"""Test get_http_response_querystring_payload"""
function = {
"name": "code_test",
"header": "api",
"method": "get",
"path": "/test/api",
"querystring": {},
"payload": {},
}
assert functions.get_http_respo... | 5,331,337 |
def _find_next_pickup_item(not_visited_neighbors, array_of_edges_from_node):
"""
Args:
not_visited_neighbors:
array_of_edges_from_node:
Returns:
"""
# last node in visited_nodes is where the traveling salesman is.
cheapest_path = np.argmin(
array_of_edges_from_node[not... | 5,331,338 |
def deformable_conv(input,
offset,
mask,
num_filters,
filter_size,
stride=1,
padding=0,
dilation=1,
groups=None,
deformable_groups=None,
... | 5,331,339 |
def ieee():
"""IEEE fixture."""
return t.EUI64.deserialize(b"ieeeaddr")[0] | 5,331,340 |
def test_no_log_none(stdin, capfd):
"""Allow Ansible to make the decision by matching the argument name
against PASSWORD_MATCH."""
arg_spec = {
"arg_pass": {}
}
am = basic.AnsibleModule(arg_spec)
# Omitting no_log is only picked up by _log_invocation, so the value never
# makes it in... | 5,331,341 |
def is_in(a_list):
"""Returns a *function* that checks if its argument is in list.
Avoids recalculation of list at every comparison."""
def check(arg): return arg in a_list
return check | 5,331,342 |
def get_log_record_extra_fields(record):
"""Taken from `common` repo logging module"""
# The list contains all the attributes listed in
# http://docs.python.org/library/logging.html#logrecord-attributes
skip_list = (
'args', 'asctime', 'created', 'exc_info', 'exc_text', 'filename',
'func... | 5,331,343 |
def make_ideal(psr):
"""Adjust the TOAs so that the residuals to zero, then refit."""
psr.stoas[:] -= psr.residuals() / 86400.0
psr.fit() | 5,331,344 |
def test_should_raise_if_wrong_key_dvc_extra_meta():
"""
Test raise if not expected keyword in dvc extra meta
"""
with pytest.raises(MlVToolException):
DocstringDvcExtra.from_meta(args=['dvc-wrong'], description='--extra p') | 5,331,345 |
def test_valid_allocation_transfer_agency(database):
"""If File C (award financial) record has a valid allocation transfer agency, rule always passes."""
cgac = CGACFactory(cgac_code='good')
af = AwardFinancialFactory(
piid='some_piid', parent_award_id='some_parent_award_id', allocation_transfer_ag... | 5,331,346 |
def test_enum():
"""Test manipulating an Enum member.
"""
e = Enum('a', 'b')
assert e.items == ('a', 'b')
assert e.default_value_mode[1] == 'a'
e_def = e('b')
assert e_def is not e
assert e_def.default_value_mode[1] == 'b'
with pytest.raises(TypeError):
e('c')
e_add = ... | 5,331,347 |
def ldap_is_intromember(member):
"""
:param member: A CSHMember instance
"""
return _ldap_is_member_of_group(member, 'intromembers') | 5,331,348 |
def test_dump_metadata(arterynetwork_def, param):
"""Test correct execution of dump_metadata.
:param arterynetwork_def: Artery network object
:param param: Config parameters
"""
an = arterynetwork_def
order, rc, qc, Ru, Rd, L, k1, k2, k3, rho, Re, nu, p0, R1, R2, CT,\
Nt, Nx, T, N_cycles... | 5,331,349 |
def details(request, slug):
"""
Show product set
"""
productset = get_object_or_404(models.ProductSet, slug=slug)
context = {}
response = []
variant_instances = productset.variant_instances()
signals.product_view.send(
sender=type(productset), instances=variant_instances,... | 5,331,350 |
def applies(platform_string, to='current'):
""" Returns True if the given platform string applies to the platform
specified by 'to'."""
def _parse_component(component):
component = component.strip()
parts = component.split("-")
if len(parts) == 1:
if parts[0] in VALID_PL... | 5,331,351 |
def _GetClassLock(cls):
"""Returns the lock associated with the class."""
with _CLASS_LOCKS_LOCK:
if cls not in _CLASS_LOCKS:
_CLASS_LOCKS[cls] = threading.Lock()
return _CLASS_LOCKS[cls] | 5,331,352 |
def _get_expression_table_name() -> TableName:
"""
Get a expression table name. This value will be switched whether
current scope is event handler's one or not.
Returns
-------
table_name : str
Target expression table name.
"""
from apysc._expression import event_handl... | 5,331,353 |
def log(config, results):
"""
analysis.py plugin: Analyze mongod.log files.
:param ConfigDict config: The global config.
:param ResultsFile results: Object to add results to.
"""
LOGGER.info("Checking log files.")
reports = config["test_control"]["reports_dir_basename"]
perf_json = conf... | 5,331,354 |
def measure_option(mode,
number=1,
repeat=1,
timeout=60,
parallel_num=1,
pack_size=1,
check_correctness=False,
build_option=None,
replay_db=None,
sav... | 5,331,355 |
def get_contributions(user, latest, org=None):
"""
Traverses the latest array,
creates a table
if org argument is present only the repos which belong to the org is added to the table
and prints the table.
"""
print("Contributions Today: ")
if latest:
table = Prett... | 5,331,356 |
def make_inference(input_data, model):
"""
input_data is assumed to be a pandas dataframe, and model uses standard sklearn API with .predict
"""
input_data['NIR_V'] = m.calc_NIR_V(input_data)
input_data = input_data.replace([np.nan, np.inf, -np.inf, None], np.nan)
input_data = input_data.dropna(... | 5,331,357 |
def property_elements(rconn, redisserver, name, device):
"""Returns a list of dictionaries of element attributes for the given property and device
each dictionary will be set in the list in order of label
:param rconn: A redis connection
:type rconn: redis.client.Redis
:param redisserver: The redis... | 5,331,358 |
def run_forever(config: Dict[str, Any]):
"""
Run and block until a signal is sent to the process.
The application, services or gRPC server are all created and initialized
when the application starts.
"""
def run_stuff(config: Dict[str, Any]):
resources = initialize_all(config)
c... | 5,331,359 |
def _dtype(a, b=None):
"""Utility for getting a dtype"""
return getattr(a, 'dtype', getattr(b, 'dtype', None)) | 5,331,360 |
def parse_garmin_tcx(filename):
""" Parses tcx activity file from Garmin Connect to Pandas DataFrame object
Args: filename (str) - tcx file
Returns: a tuple of id(str) and data(DataFrame)
DF columns=['time'(datetime.time), 'distance, m'(float), 'HR'(int),
'cadence'(int), 'speed, m/s'(int)]
"""... | 5,331,361 |
def get_decay_fn(initial_val, final_val, start, stop):
"""
Returns function handle to use in torch.optim.lr_scheduler.LambdaLR.
The returned function supplies the multiplier to decay a value linearly.
"""
assert stop > start
def decay_fn(counter):
if counter <= start:
return... | 5,331,362 |
async def is_logged(jwt_cookie: Optional[str] = Cookie(None, alias=config.login.jwt_cookie_name)):
"""
Check if user is logged
"""
result = False
if jwt_cookie:
try:
token = jwt.decode(
jwt_cookie,
smart_text(orjson.dumps(config.secret_key)),
... | 5,331,363 |
def cached_query_molecules(
client_address: str, molecule_ids: List[str]
) -> List[QCMolecule]:
"""A cached version of ``FractalClient.query_molecules``.
Args:
client_address: The address of the running QCFractal instance to query.
molecule_ids: The ids of the molecules to query.
Retur... | 5,331,364 |
def _domain_to_json(domain):
"""Translates a Domain object into a JSON dict."""
result = {}
# Domain names and bounds are not populated yet
if isinstance(domain, sch.IntDomain):
result['ints'] = {
'min': str(domain.min_value),
'max': str(domain.max_value),
'isCategorical': domain.is_... | 5,331,365 |
def draw_point(state, x, y, col=COLORS["WHITE"], symb="▓"):
"""returns a state with a placed point"""
state[y][x] = renderObject(symb, col)
return state | 5,331,366 |
def remove_read_metadata(meta, field_ids):
"""Delete any read metadata for remove fields."""
covs = defaultdict(dict)
for field_id in field_ids:
if field_id.endswith("_cov"):
if field_id.endswith("_read_cov"):
root = field_id.replace("_read_cov", "")
covs[... | 5,331,367 |
def _vars_to_add(new_query_variables, current_query_variables):
"""
Return list of dicts representing Query Variables not yet persisted
Keyword Parameters:
new_query_variables -- Dict, representing a new inventory of Query
Variables, to be associated with a DWSupport Query
current_query_vari... | 5,331,368 |
def Ak(Y2d, H, k):
"""
Calculate Ak for Sk(x)
Parameters
----------
Y2d : list
list of y values with the second derived
H : list
list of h values from spline
k : int
index from Y2d and H
Returns
-------
float
A... | 5,331,369 |
def cycle_list_next(vlist, current_val):
"""Return the next element of *current_val* from *vlist*, if
approaching the list boundary, starts from begining.
"""
return vlist[(vlist.index(current_val) + 1) % len(vlist)] | 5,331,370 |
def _cal_hap_stats(gt, hap, pos, src_variants, src_hom_variants, src_het_variants, sample_size):
"""
Description:
Helper function for calculating statistics for a haplotype.
Arguments:
gt allel.GenotypeArray: Genotype data for all the haplotypes within the same window of the haplotype to be... | 5,331,371 |
def read_cfg(file):
"""Read configuration file and return list of (start,end) tuples """
result = []
if isfile(file):
with open(file) as f:
cfg = json.load(f)
for entry in cfg:
if "start" in entry:
filter = (entry["start"], entry.get("end", None))
... | 5,331,372 |
def test_pragmas_03():
"""
Test the case where we specify a 'disable-next-line' pragma, but specify no id to disable.
"""
# Arrange
scanner = MarkdownScanner()
supplied_arguments = [
"scan",
"test/resources/pragmas/atx_heading_with_multiple_spaces_disable_with_no_id.md",
]
... | 5,331,373 |
def least_l2_affine(
source: np.ndarray, target: np.ndarray, shift: bool = True, scale: bool = True
) -> AffineParameters:
"""Finds the squared-error minimizing affine transform.
Args:
source: a 1D array consisting of the reward to transform.
target: a 1D array consisting of the target to m... | 5,331,374 |
def mark_item_as_read(
client: EWSClient, item_ids, operation="read", target_mailbox=None
):
"""
Marks item as read
:param client: EWS Client
:param item_ids: items ids to mark as read
:param (Optional) operation: operation to execute
:param (Optional) target_mailbox: target mailbox
... | 5,331,375 |
def step(state,iidx,arrayTimeIndex,globalTimeStep):
"""This is the method that will be called by the swept solver.
state - 4D numpy array(t,v,x,y (v is variables length))
iidx - an iterable of indexs
arrayTimeIndex - the current time step
globalTimeStep - a step counter that allows implementation o... | 5,331,376 |
def rerank(args: argparse.Namespace):
"""
Reranks a list of hypotheses acoording to a sentence-level metric.
Writes all output to STDOUT.
:param args: Namespace object holding CLI arguments.
"""
reranker = Reranker(args.metric)
with utils.smart_open(args.reference) as reference, utils.smar... | 5,331,377 |
def test_qualbase():
"""-q with low qualities, using ascii(quality+64) encoding"""
run("-q 10 --quality-base 64 -a XXXXXX", "illumina64.fastq", "illumina64.fastq") | 5,331,378 |
def modeling_viz_examples(df: pd.DataFrame) -> None:
"""
Purpose:
Shows examples for modeling
Args:
N/A
Returns:
N/A
"""
# classification_report example
st.write("Classification Report Example")
with st.echo():
fancylit.yellowbrick_funcs.show_classificati... | 5,331,379 |
def AIC_score(y_true, y_pred, model=None, df=None):
""" calculate Akaike Information Criterion (AIC)
Input:
y_true: actual values
y_pred: predicted values
model (optional): predictive model
df (optional): degrees of freedom of model
One of model or df is requried
"""
... | 5,331,380 |
def to_rgb(data, output=None, vmin=None, vmax=None, pmin=2, pmax=98,
categorical=False, mask=None, size=None, cmap=None):
"""Turn some data into a numpy array representing an RGB image.
Parameters
----------
data : list of DataArray
output : str
file path
vmin : float or list... | 5,331,381 |
def id_convert(values, idtype=None):
"""
Get data from the id converter API.
https://www.ncbi.nlm.nih.gov/pmc/tools/id-converter-api/
"""
base = 'http://www.pubmedcentral.nih.gov/utils/idconv/v1.0/'
params = {
'ids': values,
'format': 'json',
}
if idtype is not None:
... | 5,331,382 |
def testOneSightline(l=0., b=4., Rv=3.1, useCoarse=False):
"""Try a single sight line"""
# Import the bovy et al. map so we don't have to re-initialize it
# for each sight-line
combined19 = mwdust.Combined19()
los = lineofsight(l, b, objBovy=combined19, Rv=Rv)
if useCoarse:
los.g... | 5,331,383 |
def authenticate_user():
"""Authenticate user"""
username = request.form['username']
password = request.form['password']
user = User.query.filter_by(username=username, password=password).first()
if user is not None:
ma_schema = UserSchema()
user_data = ma_schema.dump(user)
... | 5,331,384 |
def map_signature(
r_func: SignatureTranslatedFunction,
is_method: bool = False,
map_default: typing.Optional[
typing.Callable[[rinterface.Sexp], typing.Any]
] = _map_default_value
) -> typing.Tuple[inspect.Signature, typing.Optional[int]]:
"""
Map the signature of an... | 5,331,385 |
def get_random(X):
"""Get a random sample from X.
Parameters
----------
X: array-like, shape (n_samples, n_features)
Returns
-------
array-like, shape (1, n_features)
"""
size = len(X)
idx = np.random.choice(range(size))
return X[idx] | 5,331,386 |
def _save_update(update):
"""Save one update in firestore db."""
location = {k: v for k, v in update.items() if k in _location_keys}
status = {k: v for k, v in update.items() if k in _update_keys}
# Save location in status to enable back referencing location from a status
status["location"] = _locat... | 5,331,387 |
def get_secondary_connections(network, user):
"""
Finds all the secondary connections (i.e. connections of connections)
of a given user.
Arguments:
network: the gamer network data structure.
user: a string containing the name of the user.
Returns:
A list containing the secondary connecti... | 5,331,388 |
def get_regression_function(model, model_code):
"""
Method which return prediction function for trained regression model
:param model: trained model object
:return: regression predictor function
"""
return model.predict | 5,331,389 |
def signal_handler(signal, frame):
"""Handler for Ctrl-C"""
sys.exit(0) | 5,331,390 |
def beam_motion_banding_filter(img, padding=20):
"""
:param img: numpy.array.
2d projection image or sinogram. The left and right side of the image should be
empty. So that `padding` on the left and right will be used to create an beam motion
banding image and be ... | 5,331,391 |
def Din(traceFile, cycle, accessType, memAddress):
""" Din: prints the memory reference in the "traditional
dinero" format used by the DineroIV cache simulator"""
traceFile.write("%d 0x%x\n" % (accessType, memAddress)) | 5,331,392 |
def i2c(debug=False, reset=20, req=16):
"""Yield a i2c device."""
try:
yield PN532_I2C(debug=debug, reset=reset, req=req)
finally:
GPIO.cleanup() | 5,331,393 |
def log(session):
"""Clear nicos log handler content"""
handler = session.testhandler
handler.clear()
return handler | 5,331,394 |
def load_mnist(path, kind='train'):
"""Load MNIST data from `path`"""
labels_path = os.path.join(path, '%s-labels-idx1-ubyte.gz' % kind)
images_path = os.path.join(path, '%s-images-idx3-ubyte.gz' % kind)
with gzip.open(labels_path, 'rb') as lbpath:
lbpath.read(8)
buffer = lbpath.read()
... | 5,331,395 |
def add_barostat(system):
"""Add Monte Carlo barostat"""
system.addForce(mm.MonteCarloBarostat(simulation_parameters["pressure"],
simulation_parameters["temperature"])) | 5,331,396 |
def calculate_dvh(dose_grid, label, bins=1001):
"""Calculates a dose-volume histogram
Args:
dose_grid (SimpleITK.Image): The dose grid.
label (SimpleITK.Image): The (binary) label defining a structure.
bins (int | list | np.ndarray, optional): Passed to np.histogram,
can be ... | 5,331,397 |
def build_target(output, gt_data, H, W):
"""
Build the training target for output tensor
Arguments:
output_data -- tuple (delta_pred_batch, conf_pred_batch, class_pred_batch), output data of the yolo network
gt_data -- tuple (gt_boxes_batch, gt_classes_batch, num_boxes_batch), ground truth data
... | 5,331,398 |
def dataframe_with_new_calendar(df: pd.DataFrame, new_calendar: pd.DatetimeIndex):
"""
Returns a new DataFrame where the row data are based on the new calendar (similar to Excel's VLOOKUP with
approximate match)
:param df: DataFrame
:param new_calendar: DatetimeIndex
:return: DataFrame
"""
... | 5,331,399 |
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